THSLRR: A Low-Rank Subspace Clustering Method Based on Tired Random Walk Similarity and Hypergraph Regularization Constraints.
Tian-Jing QiaoNa-Na ZhangJin-Xing LiuJunliang ShangCui-Na JiaoJuan WangPublished in: SDSC (2022)
Keyphrases
- random walk
- clustering method
- similarity measure
- graph laplacian
- proximity matrix
- hyper graph
- spectral clustering
- markov chain
- cluster analysis
- similarity matrix
- directed graph
- document clustering
- subspace clustering
- euclidean distance
- similarity metric
- distance measure
- higher order
- clustering algorithm
- link prediction
- pairwise similarities
- machine learning
- constraint satisfaction
- k means
- pairwise
- data sets
- distance function
- shortest path
- data clustering
- reinforcement learning
- feature selection